Bigated Transcranial Doppler for the Detection of Clinically Silent Circulating Emboli in Normal Persons and Patients With Prosthetic Cardiac Valves

Droste, Dirk W.; Hagedorn, Gunnar; Nötzold, A.; Siemens, Hans-Joachim; Sievers, Hans‐H.; Kaps, Manfred

doi:10.1161/01.str.28.3.588

Cited by 41 publications

(34 citation statements)

References 19 publications

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“…[13][14][15][16][17][18][19][20][21][22][23][24] In our study, the signals were reviewed by 2 observers, and for inclusion, both observers had to agree that the signal was a true embolic signal. The following definition for embolic signals was used: (1) typical visible, (2) short duration, (3) high-intensity signal, (4) within the Doppler spectrum, and (5) occurring at random within the cardiac cycle.…”

Section: Role Of Human Expertsmentioning

confidence: 99%

“…They did not have cardiac or cerebrovascular disease. In them, we performed a 6-minute series of provoked artifacts, 16 including movement of the probe, coughing, sneezing, and head rotation.…”

Section: Artifactsmentioning

confidence: 99%

“…It is widely accepted that the time delay provides useful information but is not absolutely reliable. 16,22,23,33 From our extensive experience with TCD signals, we have learned that artifacts usually have lower frequencies than emboli, and we therefore decided to use a novel time-frequency method to calculate the time delay and the main frequency of the signal pairs. For this, we chose to use the matching pursuit performed on a dictionary of Gabor functions.…”

Section: Distinction Between Artifacts and Embolimentioning

confidence: 99%

“…12 Previous attempts at producing an automated system for classifying HITS into artifacts or emboli have failed to achieve the same level of sensitivity (embolus detection) and specificity (artifact rejection) as the human expert, considered the current "gold standard." [13][14][15][16][17][18][19][20][21][22][23][24] Without an automated embolic signal detection system that is as effective as the human expert in terms of sensitivity and specificity, embolus detection remains a time-consuming process, restricted to research studies and unsuitable for clinical practice. 25 To separate artifacts from emboli, the best compromise is dual-gate TCD, which consists of tracing the embolus at 2 different depths in the same artery (time delay) ( Figure 1).…”

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confidence: 99%

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Automatic Classification of HITS Into Artifacts or Solid or Gaseous Emboli by a Wavelet Representation Combined With Dual-Gate TCD

Devuyst

Darbellay

Vesin

et al. 2001

Stroke

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Background and Purpose-Transcranial Doppler (TCD) can detect high-intensity transient signals (HITS) in the cerebralcirculation. HITS may correspond to artifacts or solid or gaseous emboli. The aim of this study was to develop an offline automated Doppler system allowing the classification of HITS. Methods-We studied 600 HITS in vivo, including 200 artifacts from normal subjects, 200 solid emboli from patients with symptomatic internal carotid artery stenosis, and 200 gaseous emboli in stroke patients with patent foramen ovale. The study was 2-fold, each part involving 300 HITS (100 of each type). The first 300 HITS (learning set) were used to construct an automated classification algorithm. The remaining 300 HITS (validation set) were used to check the validity of this algorithm. To classify HITS, we combined dual-gate TCD with a wavelet representation and compared it with the current "gold standard," the human experts. Results-A combination of the peak frequency of HITS and the time delay makes it possible to separate artifacts from emboli. On the validation set, we achieved a sensitivity of 97%, a specificity of 98%, a positive predictive value (PPV) of 99%, and a negative predictive value (NPV) of 94%. To distinguish between solid and gaseous emboli, where positive refers now to the solid emboli, we used the peak frequency, the relative power, and the envelope symmetry of HITS.On the validation set, we achieved a sensitivity of 89%, a specificity of 86%, a conditional PPV of 89%, and a conditional NPV of 89%. Conclusions-An

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Section: Role Of Human Expertsmentioning

confidence: 99%

Section: Artifactsmentioning

confidence: 99%

Section: Distinction Between Artifacts and Embolimentioning

confidence: 99%

mentioning

confidence: 99%

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Automatic Classification of HITS Into Artifacts or Solid or Gaseous Emboli by a Wavelet Representation Combined With Dual-Gate TCD

Devuyst

Darbellay

Vesin

et al. 2001

Stroke

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“…there are two possible ways of determining the detection threshold of microemboli in decibels for a given device: either by defining the range of spontaneous intensity fluctuations within the doppler signals of normal controls, or by defining fluctuations on a case-by-case basis during emboli-free periods (39,42). Spencer et al (42) reported the characteristic features of embolic signals to be transient (lasting 0.01-0.1 s), an audible chirping quality caused by their being centered on one frequency, and an intensity of up to 40 dB greater than that of the doppler signal from blood alone. One should keep in mind that not all the HItS are produced by microemboli.…”

Section: Generation Detection and Prevention Of Gaseous Microembolimentioning

confidence: 99%

Generation, Detection and Prevention of Gaseous Microemboli during Cardiopulmonary Bypass Procedure

Lou

Liu

et al. 2011

Int J Artif Organs

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Neuropsychological injury after cardiopulmonary bypass (CPB) is one of the most serious and costly complications arising from the procedure. Gaseous microemboli (GME) have long been implicated as one of the principal causes. There are two major sources of GME: surgical and manual manipulation of the heart and arteries; and the components of the extracorporeal circuit, including the type of pump, different perfusion modes, the design of the oxygenator and reservoir, and the use of vacuum assisted venous drainage (VAVD), all of which have a great impact on the delivery of existing GME to the patients. Transcranial Cranial Doppler (TCD) has been used for more than two decades to assess and monitor the quality of extracorporeal perfusion with regard to the blood flow velocity of the middle cerebral arteries (MCA) and emboli detection, contributing to the achievement of better perfusion results. The Emboli Detection and Classification (EDAC) Quantifier has been able to detect and track microemboli in CPB circuits up to 1,000 microemboli per second at flow rates ranging from 0.2 L/min to 6.0 L/min. The deleterious effects of GME are multiple, including damage to the cerebral vascular endothelium, disruption of the blood-brain barrier, complement activation, leukocyte aggregation, increased platelet adherence, and fibrin deposition in the micro-vasculature. Improvements in perfusion equipment and in perfusion and surgical techniques have led to a dramatic reduction in the occurrence of GME during cardiac surgery. Although the clinical relevance of cerebral air embolization in causing neurological damage is unclear, every single person involved in perfusion and surgical technology should be aware of the risk of embolization and strictly regulate clinical behavior. Related research should also be done to improve the design of circuit components and clinical practice with a view to eliminating air bubbles during CPB procedure.

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New Trends in Neurosonology

Devuyst¹,

Kemény²,

Despland³

2001

Current Review of Cerebrovascular Disease

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Bigated Transcranial Doppler for the Detection of Clinically Silent Circulating Emboli in Normal Persons and Patients With Prosthetic Cardiac Valves

Cited by 41 publications

References 19 publications

Automatic Classification of HITS Into Artifacts or Solid or Gaseous Emboli by a Wavelet Representation Combined With Dual-Gate TCD

Automatic Classification of HITS Into Artifacts or Solid or Gaseous Emboli by a Wavelet Representation Combined With Dual-Gate TCD

Generation, Detection and Prevention of Gaseous Microemboli during Cardiopulmonary Bypass Procedure

New Trends in Neurosonology

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